Enhancing Syndromic Surveillance With Online Respondent-Driven Detection

Area of Science:

• Epidemiology
• Public Health Surveillance
• Social Network Analysis

Background:

• Traditional infectious disease surveillance methods may miss undetected cases.
• Social networks offer a potential pathway for rapid disease information dissemination.

Purpose of the Study:

• To assess the feasibility of combining online respondent-driven detection with participatory surveillance panels.
• To explore the use of social networks for collecting infectious disease data.

Main Methods:

• Utilized a respondent-driven detection method combined with existing participatory surveillance panels in the Netherlands.
• Participants completed online surveys on upper respiratory tract infections and recruited contacts.

Main Results:

• The survey successfully spread across the Netherlands, reaching all provinces and age groups within 83 days.
• Symptomatic individuals were more likely to recruit symptomatic contacts, highlighting network effects.

Conclusions:

• Online respondent-driven detection is a feasible method for enhancing infectious disease surveillance.
• Leveraging social networks through this method improves the identification of symptomatic individuals.